1.4.4.1. Synergies and Tradeoffs between Climate Change
and Other Environmental Issues

Climate change is only one issue among many. The early stages of economic development
typically lead to an increase in many pollutants, and actions taken to reduce
one can have ancillary benefits caused by simultaneous reduction of others.
Assessments that neglect these synergies can seriously underestimate the justification
for cutbacks. On the other hand, impacts from climate change can depend on the
levels of other pollutants. For example, forests weakened by acid rain are likely
to be more vulnerable to changes in rainfall brought on by climate change or
warming, and lake acidification can have a synergy with ultraviolet radiation
penetration into the water (e.g., Schindler et al., 1996). While maintaining
its primary focus on decadal to centennial-scale climate change, Working Group
II has examined linkages among climate change and other environmental issues,
including climate variability, loss of biodiversity, deforestation, and desertification.

1.4.4.2. Synergies and Tradeoffs between Adaptation and
Mitigation

It is often argued in the literature that there is a tradeoff between adaptation
and mitigation in that resources committed to one are not available for the
other. This is debatable in practice because the people who bear emission reduction
costs or benefits often are different from those who pay for and benefit from
adaptation measures. Arguments are given on both sides of this issue. On one
hand, in a straight comparison, several factors point to the wisdom of initially
committing resources to adaptation. Insofar as no level of mitigation will completely
prevent some climate change, some adaptation will be necessary. The benefits
from adaptation are received in the country that incurs the costs, so there
is no “free-rider” problem; climate change from GHG emissions that already have
occurred means that adaptation will be required even if quite stringent mitigation
also is agreed on; many adaptation options, such as switching agricultural crops
and strengthening seawalls, are relatively cheap options for some (but not all—e.g.,
for small island states), and there may be ancillary benefits of the adaptation
action even if climatic change effects turn out to be small (e.g., “no regrets”
policies such as improving the efficiency of irrigation equipment).

On the other hand, it has been argued that climatic changes today still are
relatively small, thus there is little need for adaptation, although there is
considerable need for mitigation to avoid more severe future damages. By this
logic, it is more prudent to invest the bulk of the resources for climate policy
in mitigation, rather than adaptation.

It is reasonable to assume that many adaptation options will be pursued. This
means that the baseline against which mitigation options should be assessed
is one with adaptation also occurring. If the adaptations were effective in
reducing the costs of climatic impacts, this can significantly reduce the benefits
that otherwise would have been attributable to mitigation. On the other hand,
as Section 1.4.1 notes, lack of perfect foresight
about future climatic or other relevant social trends can lead to maladaptations.
This situation would then argue for more emphasis on mitigation because maladaptations
in the future would increase the costs of climatic impacts thus justify stronger
abatement efforts. Furthermore, it has been argued that early steps toward mitigation
can lower long-term costs of carbon abatement by reducing the rate at which
the energy-intensive capital stock has to be turned over, by inducing research
and development, and/or by enhancing learning by doing (Grubb et al., 1994;
Azar, 1998; Goulder and Schneider, 1999). Others have argued that delayed abatement
is more cost-effective because the bulk of the climate damages are likely to
occur in the future, whereas the costs of immediate abatement occur in the nearer
term; thus, discounting reduces the present value of the benefits of avoided
climate damage versus less discounted abatement costs (e.g., Wigley et al.,
1996). Working Group III explores these issues in more depth, but in the context
of the Working Group II mandate it must be recognized that many factors that
still contain considerable uncertainty enter the debate about tradeoffs between
timing and magnitudes of adaptation and mitigation efforts.

1.4.5. Integrated Assessment

Given the multi-sectoral, multi-regional, multidisciplinary, and multi-institutional
nature of the integration of climatic change assessments of effects, impacts,
and policy options, methods to perform “end-to-end” analyses have been developed
and often are labeled “integrated assessments” (see, e.g., Weyant et al., 1996;
Morgan and Dowlatabadi, 1996, and references therein). Integrated assessment
models (IAMs) have been developed to provide the logical consequences of a variety
of explicit assumptions that undergird any formal assessment technique. IAMs
seek to combine knowledge from several disciplines that is relevant to climate
change in mathematical representations of the determinants of GHG emissions,
responses of the climate system and feedbacks to emissions, effects on socioeconomic
activities and ecosystems, and potential policies and responses (Parson and
Fisher-Vanden, 1997). To date, IAMs have relied primarily on highly aggregated
representations that directly link monetized measures of projected impacts to
mean climate variables—principally, annual global mean temperature. Over time,
these sorts of estimates have been extended by introducing variation between
regions, by separating market and nonmarket damages, or by introducing other
climate variables such as precipitation (Parson and Fisher-Vanden, 1997). A
few IAMs adopt a process-based, geographically explicit approach to modeling,
thus have more detailed representation of impacts, often including changes in
physical units (e.g., crop yields) as measures of impact. These models do not
translate impacts into a common metric, such as money. This makes comparing
the level of impacts depicted in the two different modeling approaches very
difficult (Tol and Fankhauser, 1998).

IAMs have evolved from a variety of disciplinary tools that often were developed
for purposes other than assessments of climatic changes. IAMs have been classified
into a hierarchy of five levels (Schneider, 1997). This classification scheme
does not imply that each successive level of modeling along the hierarchy (see
Section 2.3.8) incorporates all of the elements at lower
levels or that incorporation of additional levels of comprehensiveness or complexity
provides more fidelity in the model’s simulation skills; that depends on the
validity of the underlying assumptions and the accuracy of methods used to formally
solve the equations that represent those assumptions. Finally, difficulties
are encountered in aggregating costs or benefits across the many categories
of impacts or opportunities, and a traceable account of any aggregations must
be paramount to maintain transparency of any analytic methods such as IAMs (see
Sections 1.5.6 and 2.6.4).

Despite these complexities, IAMs are a principal tool for studying systematic
sets of interactions that are believed to be important in explaining systems
behavior or simulating the consequences of various policies on the magnitude
and distribution of risks and benefits of climatic changes or policies to enhance
adaptation or encourage mitigation. The goal of IAMs has been to provide insights
about the possible interactions of many factors in a complex socionatural system,
rather than “answers” to specific scientific or policy questions.